Enabling Energy-Efficient and Backhaul-aware Next Generation Heterogeneous Networks

Heterogeneous networks have been firmly established as the direction in which next-generation cellular networks are evolving. We consider the dense deployment of small cells to provide enhanced capacity, while the macro cells provide wide area coverage. With the development of dual connectivity technology, deploying small cells on dedicated carriers has become an attractive option, with enhanced flexibility for splitting traffic within the network. The power consumption and latency requirements of the backhaul link are also gaining increasing prominence due to these factors. Backhaul link quality itself is expected to play an important role in influencing the deployment costs of next-generation 5G systems.  Energy efficiency as a network design paradigm is also gaining relevance due to the increasing impact cellular networks are having on the global carbon emission footprint. For operators, improving energy efficiency has the added advantage of reducing network operation expenditures. For the end-users, avoiding unnecessary draining of device battery power would improve the user experience.  In this work, we study energy efficient mechanisms for inter-frequency small cell discovery, based on mobility awareness and proximity estimation. Further, we apply generalized small cell discovery concepts in a device-to-device communication environment in order to optimize the energy consumption for device discovery. We also look at energy efficient small cell operations based on traffic characteristics and load constraints-based offloading in relation to the radio access and backhaul power consumption. In addition we study intelligent means of dist-ributing delay-critical functionalities such as Hybrid ARQ, while centralizing the computationally-intense processes in a 5G, cloud-based, centralized radio access network. Numerical evaluations done using a LTE-Advanced heterogeneous network and analytical settings indicate that significant UE and network power consumption reductions could be achieved with the considered enhancements. Using the optimized small cell operation schemes investigated in this work, reductions in network power consumption and consequent improvements in the overall energy efficiency of the network were observed. The performance of the distributed opportunistic HARQ mechanism for a centralized radio access network is compared to the optimal and static retransmission mechanisms, and the evaluated scheme is shown to perform close to the optimal mechanism, while operating with a non-ideal backhaul link

Distributed Capacity Based Multi-Channel Allocation Algorithm for Local Area Networks

The past decade has seen a vast growth in wireless communication, continuously fuelled by the users' ever-increasing demand for higher data rates. Various technologies are constantly competing with each other, trying to establish supremacy over other concurrent technologies and desperately vying to make its own space in the field of telecommunication. With the advent of 4G systems, we are at a crucial juncture. The all-important question has become: how to provide ubiquitous coverage for all the users in the network in a cost-efficient manner while at the same time satisfy high data rates and the Quality of Service (QoS) requirements proposed by ITU-R for IMT-Advanced systems? One technology which can provide an answer to the above question is low power home base stations called femtocells used for local area deployments such as residences, apartment complexes, offices, business centres and outdoor hotspot scenarios. Through this work, we propose a scalable and fully distributed solution called the Distributed Capacity Based Channel Allocation Algorithm to overcome the problem of interference management and efficient system operation in a local area environment. The proposed scheme is simple yet robust and helps Home eNodeBs select the best available radio resources which minimizes interference to the neighbouring nodes. Further, the scheme is subjected to various mitigating circumstances and interference-limited scenarios. The performance evaluation of the scheme is done under such conditions to ensure that it is scalable, flexible and can be considered as a practically viable option. Through this work, we try to not just improve the throughput experienced by the average user in a cell, but also the ones at the cell-edge who su_ers the most due to interference from the neighboring cells. The scheme proposed aims to be energy-e_cient as well by reducing the total number of component carriers used by each HeNB without compromising the average cell throughput values

Data Quality Management: Trade-offs in Data Characteristics to Maintain Data Quality

We are living in an age of information in which organizations are crumbling under the pressure of exponentially growing data. Increased data quality ensures better decision making, thereby enabling companies to stay competitive in the market. To improve data quality, it is imperative to identify all the characteristics that describe data. And, building on one characteristic results in compromising another, creating a trade-off. There are many well established and interesting theories regarding data quality and data characteristics. However, we found that there is a lack of research and literature regarding how trade-offs are handled between the different types of data that is stored by an organization. To understand how organisations deal with trade-offs, we chose a framework formulated by Eppler, where various data characteristics trade-offs are discussed. After a pre-study with experts in this field, we narrowed it down to three main data characteristic trade-offs and these were further analysed through interviews. Based on the interviews conducted and the literature review, we could prioritize data types under different data characteristics. This research gives insight to how data characteristics trade-offs should be accomplished in organizations

5G Radio Access Networks Enabling Efficient Point-to-Multipoint Transmissions

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] The first release of 5th Generation (5G) technology from 3rd Generation Project Partnership (3GPP) Rel'15 has been completed in December 2018. An open issue with this release of standards is that it only supports unicast communications in the core network and Point-To-Point (PTP) transmissions in the Radio Access Network (RAN), and does not support multicast/broadcast communications and Point-To-Multipoint (PTM) transmissions, which are 3GPP system requirements for 5G applications in a number of vertical sectors, such as Automotive, Airborne Communications, Internet-of-Things, Media & Entertainment, and Public Warning & Safety systems. In this article, we present novel mechanisms for enhancing the 5G unicast architecture with minimal footprint, to enable efficient PTM transmissions in the RAN, and to support multicast communications in the Rel'15 core as an in-built delivery optimization feature of the system. This approach will enable completely new levels of network management and delivery cost-efficiency.This work was supported in part by the European Commission under the 5G Infrastructure Public Private Partnership project "5G-Xcast: Broadcast and Multicast Communication Enablers for the Fifth Generation of Wireless Systems" (H2020-ICT-2016-2 call, grant 761498). The views expressed here are those of the authors and do not necessarily represent the project.Säily, M.; Barjau, C.; Navrátil, D.; Prasad, A.; Gomez-Barquero, D.; Tesema, FB. (2019). 5G Radio Access Networks Enabling Efficient Point-to-Multipoint Transmissions. IEEE Vehicular Technology Magazine. 14(4):29-37. https://doi.org/10.1109/MVT.2019.2936657S293714

Optimizing Over-The-Air Virtual Reality Broadcast Transmissions with Low-Latency Feedback

Virtual reality is one of the most challenging use cases in 5G due to the need for simultaneous support for high data rates, low-latency and high-reliability. In this work, we consider a radio resource efficient mechanism for the mass delivery of such content to a multitude of users with D2D augmented 5G broadcast. Based on detailed performance evaluations conducted using 5G system setting, it is shown that the optimized mechanism can provide significant gains in terms of cell-edge user throughput and resultant spectral requirements for broadcast. The performance gains are obtained due to the ability of the system to optimize the operating point, instead of targeting the worst user which has been the traditional approach for broadcast. The proposed mechanism could be an enabler for mitigating the key challenges currently foreseen for the broadcast of such immersive content

Enabling Vertical Industries Adoption of 5G Technologies:A Cartography of Evolving Solutions

5G network technologies are evolving in a tremendous pace, enhancing the potential for being adopted and exploited by vertical industries and serve advance networking requirements needs. Towards this direction, a set of 5G PPP projects are providing contributions for tackling aspects related to the overall lifecycle of 5G vertical applications design, development and deployment, including the activation and management of the appropriate network services. In this paper, a cartography of a set of novel solutions facilitating the adoption of 5G technologies by vertical industries is presented, aiming at identifying set of challenges and relevant solutions as well as potential synergies among the related projects.Grant numbers : This work was supported by the European Commission through the 5G PPP Projects, 5G-TRANSFORMER, IoRL.© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works